The present invention relates to a method of solving the registration of two images. In particular, this invention relates to a two-stage method of solving the registration of a synthetic aperture radar (SAR) image and of a forward-looking infrared (FLIR) image.
Traditional image registration systems rely on similarity between a pair of images to be registered in spatial distribution of the gray-levels using a variant of many correlation techniques. These approaches do not work when spatial gray-level distribution of the image changes between images due to different phenomenology employed by the imaging sensors, such as SAR and FLIR. Feature-based image registration techniques rely on some similarity between the extracted features (other than points) from the two images. Individual feature segments of one image can be matched against those from another using these extracted features. However, these kinds of features either rarely exist in both SAR and FLIR, or are very difficult to extract. Point-based registration techniques, on the other hand, exploit the specific configuration of a set of points in the image that satisfy the imaging models and sensor configurations under perspective transformation. This usually involves searching for a set of parameters in a multi-dimensional space, involving high computational complexity.
Registration is needed in a multi-sensor system (such as airborne sensors) to solve the correspondence or matching problem. Given a pair of SAR and FLIR images and the associated sensor models, at least 6 independent parameter values must be determined in order to register the two images. This is generally difficult without some prior knowledge about the sensor platforms (including the sensor models and the associated parameters, sensor positions and orientations). Theoretically, the two images can be registered if all the sensor parameters and sensor platform information is known. However in practice, even with the state-of-the-art sensor technology, registration is still needed due to errors and/or noise in the sensor systems or by nature of their operation. For SAR and FLIR image registration, this poses a special challenge, since there are hardly any commonly observable features in the SAR and FLIR images that can be used to correlate the two images.
Therefore, it is desirable to provide a method by which the SAR and FLIR images can be registered with low computational complexity and high robustness.
This invention relates to a method of solving the registration of a synthetic aperture radar (SAR) image and of a forward-looking infared (FLIR) image based on feature points detectable from both images. The method is distinguished by two stages: an initial registration stage and a residual registration stage. In the initial registration, feature points detected from the FLIR image are transformed into the SAR image coordinates. In the residual registration stage, the set of feature points from SAR and that from FLIR undergo a generalized Hough transform (GHT) from which a maximal subset of matching points is obtained and the registration transformation can be derived. The method in the present invention allows the second stage residual registration, with the method used in the first stage, to be done in a two-dimension (2-D) GHT, rather than in higher dimensions.
Using available sensor parameters and sensor location information, the registration task can be separated into 5 steps: (1) detecting feature points from both the SAR and the FLIR image; (2) transforming the feature points from the FLIR image into the SAR image using known sensor parameters and sensor platform information; (3) carrying out the GHT for the set of SAR feature points and the set of transformed FLIR feature points in 2-D translation domain, and select the maximal subset of the matching feature points from the GHT; (4) computing the updated registration transformation; and (5) evaluating the registration transformation. As a result, the present invention provides both an image registration transformation that aligns the SAR and the FLIR and a set of corresponding point pairs between the SAR and the FLIR images. The reduction of registration search space involved in the registration is from six to two dimensions. Consequences of this reduction include a substantial reduction in the possibility of false registration and robust registration against noise and error introduced during data collection This method also works in cases where the matching set of feature points constitute only a very small portion of the total feature point population in both SAR and FLIR images, with the rest being caused by random clutter in the scene.